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Olfactory Processing as a Function of Population and Pathway Anatomy

  • Author(s): Glenn-Hall, Tiffany
  • Advisor(s): Bazhenov, Maxim
  • et al.
Creative Commons Attribution 4.0 International Public License
Abstract

From odors in the environment to a behavior in response to those odors there are a lot of brain structures and neural populations involved in make critical decisions. Understanding how odor representation and classification changes across each neural population and individual neurons is important for building a case of what each population is doing. Olfactory sensory neurons (OSNs) project to the antennal lobe (AL) in the insect brain. Projection neurons (PNs) from the AL project to the mushroom body (MB) and lateral horn (LH). We created a model of the locust AL, MB, and LH. Odors were best classified when the entire neural population was taken in to account. Performance also improved with increased stimulus duration. There is research supporting a single large inhibitory neuron, which uses feedback inhibition to inhibit all the kenyon cells (KCs) in the MB. We created two models one using feedback inhibition and one using feed-forward. We found the inhibitory network determined when each neuronal population were most active in comparison to the AL local field potential oscillation. From odors in the environment to a behavior in response to those odors there are a lot of brain structures and neural populations involved in make critical decisions. Understanding how odor representation and classification changes across each neural population and individual neurons is important for building a case of what each population is doing. Olfactory sensory neurons (OSNs) project to the antennal lobe (AL) in the insect brain. Projection neurons (PNs) from the AL project to the mushroom body (MB) and lateral horn (LH). We created a model of the locust AL, MB, and LH. Odors were best classified when the entire neural population was taken in to account. Performance also improved with increased stimulus duration. There is research supporting a single large inhibitory neuron, which uses feedback inhibition to inhibit all the kenyon cells (KCs) in the MB. We created two models one using feedback inhibition and one using feed-forward. We found the inhibitory network determined when each neuronal population were most active in comparison to the AL local field potential oscillation.

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